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Quantification of measurable residual disease using duplex sequencing in adults with acute myeloid leukemia

Dillon, L. W.; Higgins, J.; Nasif, H.; Othus, M.; Beppu, L.; Smith, T. H.; Schmidt, E.; Valentine, C. C.; Salk, J. J.; Wood, B. L.; Erba, H. P.; Radich, J. P.; Hourigan, C. S.

2023-03-27 oncology
10.1101/2023.03.26.23287367
Show abstract

The presence of measurable residual disease (MRD) is strongly associated with treatment outcomes in acute myeloid leukemia (AML). Despite the correlation with clinical outcomes, MRD assessment has yet to be standardized or routinely incorporated into clinical trials. Discrepancies have been observed between different techniques for MRD assessment and there remains a need to compare centralized, high-quality multiparametric flow cytometry (MFC) and ultrasensitive next-generation sequencing (NGS) in AML patients with diverse mutational profiles. In 62 patients with AML, aged 18-60, in first complete remission after intensive induction therapy on the randomized phase 3 SWOG-S0106 clinical trial, MRD detection by MFC was compared with a 29 gene panel utilizing duplex sequencing (DS), an NGS method that generates double-stranded consensus sequences to reduce false positive errors. Using DS, detection of a persistent mutation utilizing defined criteria was seen in 22 (35%) patients and was strongly associated with higher rates of relapse (68% vs 13% at year 5; HR, 8.8; 95% CI, 3.2-24.5; P<0.001) and decreased survival (32% vs 82% at year 5; HR, 5.6; 95% CI, 2.3-13.8; P<0.001). MRD as defined by DS strongly outperformed MFC, which was observed in 10 (16%) patients and marginally associated with higher rates of relapse (50% vs 30% at year 5; HR, 2.4; 95% CI, 0.9-6.7; P=0.087) and decreased survival (40% vs 68% at year 5; HR, 2.5; 95% CI, 1.0-6.3; P=0.059). Furthermore, the prognostic significance of DS MRD status at the time of remission was similar on both randomized arms of the trial, predicting S0106 clinical trial outcomes. These findings suggest that DS is a powerful tool that could be used in patient management and for early treatment assessment in clinical trials.

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